Document Type : علمی - پژوهشی
Authors
1
M.Sc. Student of Remote Sensing and GIS, Department of Environment and Energy, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2
Associate Professor of Remote sensing and GIS Group, Department of Environment and Energy, Science and Research Branch, Islamic Azad University, Tehran, Iran.
3
Associate Professor of Water Sciences and Engineering Department, Faculty of Engineering and Technology, Imam Khomeini International University, Qazvin, Iran.
Abstract
Calculating the canopy temperature and land surface temperatureusing satellite imagery is very attractive to estimate actual evapotranspiration (ET) by energy balance algorithm. In studies, to evaluate ET, the accuracy of the calculated thermal gradient between surface and air, as well as temperature difference between various land covers is very important. To calculate land surface temperature (LST) in Shahr-E-Kord plain, the study area, there were three principal challenges. First, the absence of enough studies about calculating LST using Landsat8 thermal bands, the second, lack of canopy temperature and land surface temperature observed data, and finally, the only available data for surface temperature was minimum daily surface temperature in the climatology and synoptic stations. In this study, in order to convert the surface brightness temperature to the LST, the split-window algorithm of NOAA-AVHRR was used. Also, the proposed SEBAL algorithm was applied to calculate the surface emissivity. Due to the lack of the reference weather stations, after calculating LST at the satellite overpass time in non-reference weather stations, the deviation error calculation method was used to calibrate satellite LST and to prepare daily LST layers. Results showed that all calculated correlation coefficients were more than 0.9. Also, all existing regression relations were significant at 95% and even 99% level of confidence. In different day-images, maximum difference of calculated deviation errors was less than 0.5 K and, the calculated RMSEs were between 1.9 to 2.2 K, acceptable comparing to similar studies.
Keywords
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